randomizeR (version 3.0.2)

getExpectation: Get expectations of a randomization list

Description

Generates a matrix of the expectations of the included patients in the clinical trial.

Usage

getExpectation(randSeq, issue, endp)
# S4 method for randSeq,missing,survEndp
getExpectation(randSeq, endp)
# S4 method for randSeq,missing,expEndp
getExpectation(randSeq, endp)
# S4 method for randSeq,missing,normEndp
getExpectation(randSeq, endp)
# S4 method for randSeq,power,normEndp
getExpectation(randSeq, issue, endp)
# S4 method for randSeq,chronBias,normEndp
getExpectation(randSeq, issue, endp)
# S4 method for randSeq,chronBias,expEndp
getExpectation(randSeq, issue, endp)
# S4 method for randSeq,chronBias,survEndp
getExpectation(randSeq, issue, endp)
# S4 method for randSeq,chronBias,missing
getExpectation(randSeq, issue)
# S4 method for randSeq,selBias,normEndp
getExpectation(randSeq, issue, endp)
# S4 method for randSeq,selBias,expEndp
getExpectation(randSeq, issue, endp)
# S4 method for randSeq,selBias,survEndp
getExpectation(randSeq, issue, endp)
# S4 method for randSeq,selBias,missing
getExpectation(randSeq, issue)
# S4 method for randSeq,combinedBias,normEndp
getExpectation(randSeq, issue, endp)
# S4 method for randSeq,combinedBias,expEndp
getExpectation(randSeq, issue, endp)
# S4 method for randSeq,combinedBias,survEndp
getExpectation(randSeq, issue, endp)
# S4 method for randSeq,combinedBiasStepTrend,normEndp
getExpectation(randSeq, issue, endp)
# S4 method for randSeq,combinedBiasStepTrend,expEndp
getExpectation(randSeq, issue, endp)
# S4 method for randSeq,combinedBiasStepTrend,survEndp
getExpectation(randSeq, issue, endp)

Value

A matrix of the expectations of the included patients in the clinical trial.

Arguments

randSeq

object of the class randSeq.

issue

object of the class issue (optional).

endp

object of the class endpoint (optional).

Details

It is assumed that the expectations of the included patients in a clinical trial can be influenced in three different ways:

• The strength of selection bias and the guessing strategy of the investigator (see selBias).

• The strength of a linear time trend, which is described by an object of the class chronBias.

• The expectations of the investigated treatment groups can be different (see e.g. normEndp).

Examples

# get Expectation for a normal endpoint
myPar <- bsdPar(10, 2)
M <- genSeq(myPar, 2)
cs <- selBias("CS", 2, "sim")
endp <- normEndp(mu = c(2, 2), sigma = c(1, 1))
getExpectation(M, cs, endp)

# get Expectation for an exponential endpoint
cs <- selBias("CS", 0.1 , "sim")
endp <- expEndp(lambda = c(0.5, 1), cenTime = 10, cenRate = 0.01)
getExpectation(M, cs, endp)